A BCI Driving System to Understand Brain Signals Related to Steering

Enrico Zero, Simone Graffione, Chiara Bersani, Roberto Sacile

2021

Abstract

In the last years, the manufactured vehicles were designed to focus on prevention of some risky situations caused by a human driver. The aim of this paper is to illustrate the design and implementation of a BCI system which can detect the arm movements by the EEG signal during a simulated driving session. The proposed approach to realize a classifier able to recognize the arm movement by EEG feature analysis is based on the consecutive application of a Time Delay Neural Network (TDNN) and a Pattern Recognition Neural Network (PRNN). Preliminary tests are shown on three different participants between 24 and 45 years old.

Paper Citation

in Harvard Style

Zero E., Graffione S., Bersani C. and Sacile R. (2021). A BCI Driving System to Understand Brain Signals Related to Steering. In Proceedings of the 18th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-522-7, pages 745-751. DOI: 10.5220/0010576807450751

in Bibtex Style

@conference{icinco21,
author={Enrico Zero and Simone Graffione and Chiara Bersani and Roberto Sacile},
title={A BCI Driving System to Understand Brain Signals Related to Steering},
booktitle={Proceedings of the 18th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2021},
pages={745-751},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010576807450751},
isbn={978-989-758-522-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - A BCI Driving System to Understand Brain Signals Related to Steering
SN - 978-989-758-522-7
AU - Zero E.
AU - Graffione S.
AU - Bersani C.
AU - Sacile R.
PY - 2021
SP - 745
EP - 751
DO - 10.5220/0010576807450751